Instructions to use tdro-llm/s2-tdro-Qwen1.5-1.8B-curr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tdro-llm/s2-tdro-Qwen1.5-1.8B-curr with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tdro-llm/s2-tdro-Qwen1.5-1.8B-curr") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 727 Bytes
3521118 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | {
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"base_model_name_or_path": "Qwen/Qwen1.5-1.8B",
"bias": "none",
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"inference_mode": true,
"init_lora_weights": true,
"layer_replication": null,
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"layers_to_transform": null,
"loftq_config": {},
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"megatron_config": null,
"megatron_core": "megatron.core",
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"peft_type": "LORA",
"r": 8,
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"target_modules": [
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"task_type": "FEATURE_EXTRACTION",
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} |